Bottom Line:
This disorder constitutes one of the most common causes of disability worldwide, and as a result, it has a severe socioeconomic impact.The information registered by the sensors is processed and managed by a mobile application that facilitates the expert's normal routine, while reducing the impact of human errors and expediting the analysis of the test results.The results of this study prove the reliability of mDurance and further demonstrate that practitioners are certainly interested in the regular use of a system of this nature.

ABSTRACTLow back pain is the most prevalent musculoskeletal condition. This disorder constitutes one of the most common causes of disability worldwide, and as a result, it has a severe socioeconomic impact. Endurance tests are normally considered in low back pain rehabilitation practice to assess the muscle status. However, traditional procedures to evaluate these tests suffer from practical limitations, which potentially lead to inaccurate diagnoses. The use of digital technologies is considered here to facilitate the task of the expert and to increase the reliability and interpretability of the endurance tests. This work presents mDurance, a novel mobile health system aimed at supporting specialists in the functional assessment of trunk endurance by using wearable and mobile devices. The system employs a wearable inertial sensor to track the patient trunk posture, while portable electromyography sensors are used to seamlessly measure the electrical activity produced by the trunk muscles. The information registered by the sensors is processed and managed by a mobile application that facilitates the expert's normal routine, while reducing the impact of human errors and expediting the analysis of the test results. In order to show the potential of the mDurance system, a case study has been conducted. The results of this study prove the reliability of mDurance and further demonstrate that practitioners are certainly interested in the regular use of a system of this nature.

Mentions:
The first part of this evaluation aims at estimating the inter-rater reliability between the traditional trunk endurance assessment and mDurance. For that purpose, the results of the experiment, i.e., the times measured for each individual, test and procedure are contrasted (Table 2). As can be observed, the results obtained through both traditional and mDurance methods are generally in line, which reflects the utility of the developed system. However, to support this observation, a formal statistical analysis is required. To that end, the intraclass correlation coefficient (ICC) (ρ) [80] Cronbach's α estimator [81] and the Bland–Altman “limits of agreements” statistic for continuous variables [82] are considered here. These statistics are widely utilized in the clinical domain to evaluate the agreement among two different instruments or two measurements techniques. One-way random effects ICC(ρ) and its confidence intervals (CI) are calculated for the inter-rater reliability trials. In accordance with previous studies [15,17], an ICC (ρ) value of less than 0.4 reflects poor inter-rater reliability; 0.4 to 0.75 represents fair to good reliability; and more than 0.75 is considered an excellent reliability. Similarly, a Cronbach's α statistic less than 0.5 is considered unacceptable; 0.5 to 0.6 is poor; 0.6 to 0.7 is questionable; 0.7 to 0.8 is acceptable; 0.8 to 0.9 is good; and a value greater than 0.9 represents an excellent reliability [83]. Finally, the Bland–Altman graphical technique is used to plot the differences between the measurements of the two procedures against their averages, which helps to better understand the agreement between both methods [84]. The results of the analysis are shown in Table 3 and Figure 6. SPSS Version 21.0 (IBM Corporation, Armonk, NY) is used for all of the statistical analyses.

Mentions:
The first part of this evaluation aims at estimating the inter-rater reliability between the traditional trunk endurance assessment and mDurance. For that purpose, the results of the experiment, i.e., the times measured for each individual, test and procedure are contrasted (Table 2). As can be observed, the results obtained through both traditional and mDurance methods are generally in line, which reflects the utility of the developed system. However, to support this observation, a formal statistical analysis is required. To that end, the intraclass correlation coefficient (ICC) (ρ) [80] Cronbach's α estimator [81] and the Bland–Altman “limits of agreements” statistic for continuous variables [82] are considered here. These statistics are widely utilized in the clinical domain to evaluate the agreement among two different instruments or two measurements techniques. One-way random effects ICC(ρ) and its confidence intervals (CI) are calculated for the inter-rater reliability trials. In accordance with previous studies [15,17], an ICC (ρ) value of less than 0.4 reflects poor inter-rater reliability; 0.4 to 0.75 represents fair to good reliability; and more than 0.75 is considered an excellent reliability. Similarly, a Cronbach's α statistic less than 0.5 is considered unacceptable; 0.5 to 0.6 is poor; 0.6 to 0.7 is questionable; 0.7 to 0.8 is acceptable; 0.8 to 0.9 is good; and a value greater than 0.9 represents an excellent reliability [83]. Finally, the Bland–Altman graphical technique is used to plot the differences between the measurements of the two procedures against their averages, which helps to better understand the agreement between both methods [84]. The results of the analysis are shown in Table 3 and Figure 6. SPSS Version 21.0 (IBM Corporation, Armonk, NY) is used for all of the statistical analyses.

Bottom Line:
This disorder constitutes one of the most common causes of disability worldwide, and as a result, it has a severe socioeconomic impact.The information registered by the sensors is processed and managed by a mobile application that facilitates the expert's normal routine, while reducing the impact of human errors and expediting the analysis of the test results.The results of this study prove the reliability of mDurance and further demonstrate that practitioners are certainly interested in the regular use of a system of this nature.

ABSTRACTLow back pain is the most prevalent musculoskeletal condition. This disorder constitutes one of the most common causes of disability worldwide, and as a result, it has a severe socioeconomic impact. Endurance tests are normally considered in low back pain rehabilitation practice to assess the muscle status. However, traditional procedures to evaluate these tests suffer from practical limitations, which potentially lead to inaccurate diagnoses. The use of digital technologies is considered here to facilitate the task of the expert and to increase the reliability and interpretability of the endurance tests. This work presents mDurance, a novel mobile health system aimed at supporting specialists in the functional assessment of trunk endurance by using wearable and mobile devices. The system employs a wearable inertial sensor to track the patient trunk posture, while portable electromyography sensors are used to seamlessly measure the electrical activity produced by the trunk muscles. The information registered by the sensors is processed and managed by a mobile application that facilitates the expert's normal routine, while reducing the impact of human errors and expediting the analysis of the test results. In order to show the potential of the mDurance system, a case study has been conducted. The results of this study prove the reliability of mDurance and further demonstrate that practitioners are certainly interested in the regular use of a system of this nature.